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Ioannis Ν. Daliakopoulos

Hellenic Mediterranean University

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Ioannis K. Tsanis

Technical University of Crete

Aristeidis Koutroulis

Technical University of Crete

Manolis Grillakis

Technical University of Crete

Thrassyvoulos Manios

Hellenic Mediterranean University

Gudrun Schwilch

University of Bern

Rudi Hessel

Wageningen University & Research

Artemi Cerdà

Universitat de València

Aristides Moustakas

Natural History Museum

Christina Chroni

Harokopio University of Athens

Silvia Kohnová

Slovak University of Technology in Bratislava

Cooperative Institutions

Technical University of Crete

Wageningen University & Research

Hellenic Mediterranean University

University of Leeds

Foundation for Research and Technology Hellas

University of Alicante

Vrije Universiteit Amsterdam

Mediterranean Agronomic Institute of Chania

University of Bern

Centre National de la Recherche Scientifique

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Long-term monitoring of soil bulk density and erosion rates in two Prunus Persica (L) plantations under flood irrigation and glyphosate herbicide treatment in La Ribera district, Spain

Journal of Environmental Management (2021)

Artemi Cerdà Ioannis Ν. Daliakopoulos Enric Terol Agata Novara Yalda Fatahi

10.1016/j.jenvman.2021.111965

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Citations (37)

Monitoring soil erosion with means of sediment fences and Earth Observation in Crete, Greece

EGU General Assembly Conference Abstracts (2018)

Dimitrios D. Alexakis Ioannis Ν. Daliakopoulos Ioannis K. Tsanis

Source

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Citations (0)

Regionalizing Root‐Zone Soil Moisture Estimates From ESA CCI Soil Water Index Using Machine Learning and Information on Soil, Vegetation, and Climate

Water Resources Research (2021)

Manolis Grillakis Aristeidis Koutroulis Dimitrios D. Alexakis Christos Polykretis Ioannis Ν. Daliakopoulos

Abstract The European Space Agency (ESA), through the Climate Change Initiative (CCI), is currently providing nearly 4 decades of global satellite‐observed, fully homogenized soil moisture data for the uppermost 2–5 cm of the soil layer. These data are valuable as they comprise one of the most complete remotely sensed soil moisture data sets available in time and space. One main limitation of the ESA CCI soil moisture data set is the limited soil depth at which the moisture content is represented. In order to address this critical gap, we (a) estimate and calibrate the Soil Water Index using ESA CCI soil moisture against in situ observations from the International Soil Moisture Network and then (b) leverage machine learning techniques and physical soil, climate, and vegetation descriptors at a global scale to regionalize the calibration. We use this calibration to assess the root‐zone soil moisture for the period 2001–2018. The results are compared against the European Centre for Medium‐Range Weather Forecasts, ERA5 Land, and the Famine Early Warning Systems Network Land Data Assimilation System reanalyses soil moisture data sets, showing a good agreement, mainly over mid latitudes. This work contributes to the exploitation of ESA CCI soil moisture data, while the produced data can support large‐scale soil moisture‐related studies.

Pedotransfer function

10.1029/2020wr029249

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Citations (40)

Data-driven competitive facilitative tree interactions and their implications on nature-based solutions

The Science of The Total Environment (2018)

Aristides Moustakas Ioannis Ν. Daliakopoulos Tim G. Benton

Tree (set theory)

Facilitation

Density dependence

10.1016/j.scitotenv.2018.09.349

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Citations (9)

Impact of climate change on water resources status: A case study for Crete Island, Greece

Journal of Hydrology (2012)

Aristeidis Koutroulis Ioannis K. Tsanis Ioannis Ν. Daliakopoulos Daniela Jacob

Water security

Representative Concentration Pathways

10.1016/j.jhydrol.2012.11.055

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Citations (130)

Cross sectoral impacts on water availability at +2 °C and +3 °C for east Mediterranean island states: The case of Crete

Journal of Hydrology (2015)

Aristeidis Koutroulis Manolis Grillakis Ioannis Ν. Daliakopoulos Ioannis K. Tsanis Daniela Jacob

10.1016/j.jhydrol.2015.11.015

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Citations (52)

The challenge of unprecedented floods and droughts in risk management

Nature (2022)

Heidi Kreibich Anne F. Van Loon Kai Schröter Philip J. Ward Maurizio Mazzoleni

Risk management has reduced vulnerability to floods and droughts globally1,2, yet their impacts are still increasing3. An improved understanding of the causes of changing impacts is therefore needed, but has been hampered by a lack of empirical data4,5. On the basis of a global dataset of 45 pairs of events that occurred within the same area, we show that risk management generally reduces the impacts of floods and droughts but faces difficulties in reducing the impacts of unprecedented events of a magnitude not previously experienced. If the second event was much more hazardous than the first, its impact was almost always higher. This is because management was not designed to deal with such extreme events: for example, they exceeded the design levels of levees and reservoirs. In two success stories, the impact of the second, more hazardous, event was lower, as a result of improved risk management governance and high investment in integrated management. The observed difficulty of managing unprecedented events is alarming, given that more extreme hydrological events are projected owing to climate change3.

Flood risk management

Vulnerability

10.1038/s41586-022-04917-5

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Citations (281)

Application of solar drying as a pre-treatment method for storing wet feedstocks prior to use in anaerobic digesters: Effect on methane production and digestate composition

Fuel (2023)

Nikolaos Papastefanakis Ioannis Ν. Daliakopoulos Angeliki Maragkaki Christos Tsompanidis Νικόλαος Ζώτος

Digestate

Biogas

Mesophile

Hydraulic retention time

Cow dung

10.1016/j.fuel.2023.128477

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Citations (2)

Comparison of an artificial neural network and a conceptual rainfall–runoff model in the simulation of ephemeral streamflow

Hydrological Sciences Journal (2016)

Ioannis Ν. Daliakopoulos Ioannis K. Tsanis

The rainfall–runoff process is governed by parameters that can seldom be measured directly for use with distributed models, but are rather inferred by expert judgment and calibrated against historical records. Here, a comparison is made between a conceptual model (CM) and an artificial neural network (ANN) for their ability to efficiently model complex hydrological processes. The Sacramento soil moisture accounting model (SAC-SMA) is calibrated using a scheme based on genetic algorithms and an input delay neural network (IDNN) is trained for variable delays and hidden layer neurons which are thoroughly discussed. The models are tested for 15 ephemeral catchments in Crete, Greece, using monthly rainfall, streamflow and potential evapotranspiration input. SAC-SMA performs well for most basins and acceptably for the entire sample with R2 of 0.59–0.92, while scoring better for high than low flows. For the entire dataset, the IDNN improves simulation fit to R2 of 0.70–0.96 and performs better for high flows while being outmatched in low flows. Results show that the ANN models can be superior to the conventional CMs, as parameter sensitivity is unclear, but CMs may be more robust in extrapolating beyond historical record limits and scenario building.EDITOR M.C. Acreman; ASSOCIATE EDITOR not assigned

Ephemeral key

Hydrological modelling

10.1080/02626667.2016.1154151

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Citations (75)

Managing Household Food Waste with the FoodSaveShare Mobile Application

Sustainability (2024)

George Mastorakis Ioannis Kopanakis John Makridis Christina Chroni Katerina Synani

It is estimated that European households are responsible for 55% of food waste generation. Key factors contributing to household food waste generation include food spoilage, confusion over expiration dates, overbuying, and inadequate shopping planning. Thus, food waste prevention at the household level depends heavily on food supplies monitoring and management. To this end, during the last decade, several consumer-oriented digital tools have been designed and launched. A literature review showed that currently accessible digital tools are scarce and cover a narrow range of functionalities. Here, we address these issues by designing and launching a decision support tool implemented in a smart mobile phone application (app), the FoodSaveShare Mobile App. The application development followed a traditional client–server architecture using state-of-the-art software and hardware technologies. Additionally, a survey of 340 individuals was conducted to better understand end-user motivation for and barriers against adopting this and similar apps. The developed application combines user-provided data with a retailer loyalty program to leverage the integrated features for tracking shopping activities. The app features a household shopping list populated by product barcode scanning and manual entry. Based on food and packaging type, food products are assigned approximate expiration dates to issue product expiration reminders. For products about to expire, suggestions for their utilization are provided, drawing from a list of over 7000 recipes. Additional functionality allows users to identify products that have either been consumed in time or that need to be discarded. Analytical tools, such as past purchase and resources discarded versus resources saved statistics, offer comprehensive insight and encourage improved shopping and consumption practices. The FoodSaveShare App was launched during the A2UFood Project, which allowed an organised campaign for its use. The app was tested under real customer data and conditions, and selected features have been adopted by the largest supermarket chain on the Island of Crete, Greece. The potential end-user survey results suggest that, provided personal data use issues are addressed, such apps can have a significant impact on reducing household food waste. Future work will focus on analysing the datasets produced by the application to assess its impact on household food waste management.

Food Waste

10.3390/su16072800

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Citations (5)